The designs for Stage 1, 2, 3 accounted for the given building geometry constraints of 2,500,000 to 3,000,000 SF of new floor area and accounted for the site development limits of up to 984 feet wide and 328 deep in the plan view as well as being no taller than the site’s height limitation of 755 feet.
Stage 1 – Creating Forms with Revit Conceptual Masses
Part 1: The building model was set up to be flexed and tested using the Revit conceptual mass form example with Twisting Triangular Mass. The project location was set to Dubai, UAE which is important for determining both the sun’s location and local climate conditions. To allow for computation for the gross floor area of the building, levels were added and the mass element was divided into mass floors. The mass elements became visible by turning on the command for mass forms and floors. To create the building form’s outer shape, I imported Twisting Triangular Mass conceptual mass element into the Revit project. The form’s instance parameters for constant values were specified to achieve the desired shape shown in Figure 1. The dimensions consist of top height, top rotation, top radius, mid rotation, mid height, base rotation, and base radius. The Dynamo graph logic was built to allow flexing of one of the building form’s input parameters (Mid Rotation). The model element was selected from Revit and the report parameters’ names were set up. A Dynamo List.Map was also set up to allow for iterative evaluation of the range of values (0 to 75 degrees by an increment of 15 degrees) for the Mid Rotation input parameter. The logic set up uses a custom node (“BuildingForm.EvaluateSingleInput_3parameters”) to test each case; one of the inputs (parameterValuesToTest) remains empty so that the test values will be filled with the List.Map. The report parameter names, building form element, as well as the name for the parameter to test are specified as inputs to the custom node. After the input parameter values are set and Revit element is updated, the custom node gets the desired parameter values and provides outputs for those parameters. The series was run for 6 test cases and the corresponding model geometries are shown in Figure 1. After each case is tested and corresponding parameter has its results reported, the resulting evaluation metrics (gross floor area, gross surface area, gross volume) were exported to the specified file paths using the Data.ExportToExcel node to the following output files:
- 4units_Stephanie Chang_Module5_Stage1_Part1_GrossFloorArea
- 4units_Stephanie Chang_Module5_Stage1_Part1_GrossVolume
- 4units_Stephanie Chang_Module5_Stage1_Part1_GrossSurfaceArea
Part 2: I created a new Revit conceptual mass family to represent the outer shape of my building form; the newly created Autodesk Revit family file is called: “Asymmetric Twisting Tower.” I created parametrically flexible floor footprints and had the profiles placed at specified levels followed by lofting to achieve the overall desired building form. Dimensions included top rotation, top width, top depth, top height, mid rotation, mid depth, mid width, mid height, base rotation, base width, and base depth. Using the same Dynamo logic applied in Part 1 for the evaluation of this new building form, the input parameter (Mid Rotation) was flexed for a new range of values: 0 to 45 degrees by an increment of 5 degrees. The series was run for 10 test cases with the resulting model geometries shown in Figure 2. The new building form’s resulting evaluation metrics (gross floor area, gross surface area, gross volume) were exported using the Data.ExportToExcel node to the following output files:
- 4units_Stephanie Chang_Module5_Stage1_Part2_GrossFloorArea
- 4units_Stephanie Chang_Module5_Stage1_Part2_GrossVolume
- 4units_Stephanie Chang_Module5_Stage1_Part2_GrossSurfaceArea
The compiled results of the input parameters and output evaluation metrics for Stage 1’s Part 1 and Part 2 are summarized in the following file:
- 4units_Stephanie Chang_Module5_Stage1_Part1 & Part2 Compiled GrossFloorArea_GrossVolume_GrossSurfaceArea
Point to Ponder: The advantage of exporting the values to Excel is that the table for each parameter is created automatically to the specified path file. This allows the table to be updated automatically when the analysis needs to be re-run for different input parameters.
Creative bonus:
- The series in Part 2 is run for 10 test cases and uses a very unique building form for the evaluation.
- There is an option to export the data for the output evaluation metrics as Excel or CSV files
Stage 2 – Creating Forms with Dynamo or Grasshopper Geometry
I created a Grasshopper graph to model my proposed building form’s outer shape. Parametrically flexible profiles were created as floor footprints. There is a total of 5 ellipses (base ellipse, ellipses at 0.25 x height, 0.5 x height, 0.75 x height, top ellipse) which are scaled, translated, and rotated per specifications. The base ellipse has fixed radius specified as 250 and 150 ft in the X and Y directions respectively. A constant scaling factor of 0.4 is applied for the middle ellipses positioned at elevations of 0.25 x height, 0.5 x height, 0.75 x height. Two inputs (Height, Top Scaling Factor) were flexed to evaluate the new building form. The values for these two flexible inputs are specified in an excel file (“4units_Stephanie Chang_Module5_Stage2_Design Space for GH”).
These scaled, translated, and rotated ellipse profiles have their data streams merged and subsequently lofted to achieve a surface and volume that represents the overall new building form. The lofted surface, bottom surface, and top surface are used in the calculation of the evaluation metrics (gross floor area, gross surface area, gross volume). The building volume is calculated by merging the data streams of the bottom surface, lofted surface, and top surface and using this as the input to the brep join node whose output is fed into the volume node. The façade surface area is found by finding the sum of the loft surface and top surface. To find the floor area, a plane is first created with reference to the vertical offsets (levels); this is used as an input in addition to the lofted surfaces to solve the intersection events for the brep and plane. The output of this section node is used as an input for creating a patch surface whose area of the geometry is fed into the mass addition node to compute the floor area.
Grasshopper Anemone loop start and loop end nodes were used for the iterative evaluation of the combinations of the input parameters (2 of them are flexible: height and top scaling factor). A total of 12 test cases were run in the series with height ranging from 700 to 750 ft and top scaling factor ranging from 0.6 to 0.9. The resulting geometries are shown in Figure 3.
The Excel writeout of the corresponding output evaluation metrics are reported in:
- 4units_Stephanie Chang_Module5_Stage2_Design Space for GH_output
The compiled summary table with both input and output evaluation metrics are reported in the following file:
- 4units_Stephanie Chang_Module5_Stage2_Compiled Inputs & Outputs
Point to Ponder: All 12 test cases meet the floor area requirement (results span from 2.72 to 2.93 million SF) as well as height requirement (<755 ft). Holding height constant for varied top scaling factor conditions, a change of 0.1 for the top scaling factor leads to a significant shift in the façade surface area. For instance, at a height of 700 ft, a reduction in scaling factor from 0.9 to 0.8 leads to a drop in façade surface area by ~35,703 SF. Similarly, at a height of 730 ft, a reduction in scaling factor from 0.9 to 0.8 results in ~35,641 SF reduction in façade surface area. For a height of 720 ft, reducing the scaling factor from 0.7 to 0.6 results in ~40,549 SF reduction in the façade surface area. From the flexed 2-input parameter evaluation, this suggests that the flexed input (top scaling factor of the top ellipse) had the biggest effect of the two-flexed inputs on creating the desirable building form by minimizing the façade surface area (impacts building performance). By comparison, under the given constraints for total floor area and maximum height, varying the height at similar top scaling factors had a lesser impact on the façade surface area.
Stage 3 – Summarizing the Testing Results
I added new node logic to allow for the computation of a fourth metric (gross floor area created / gross surface area of the building envelope). I then re-evaluated the test cases and identified the pair of input values (height value, top scaling factor) that give the maximum (5.52) and minimum (4.82) value of this new metric to be (height value: 740 ft, top scaling factor: 0.7) and (height value: 720 ft, top scaling factor: 0.7) respectively. Node logic was also added to identify the indices of the fourth metric’s maximum and minimum values, which were then used to determine the corresponding pairs of input values (height, top scaling factor).
The same excel file from Stage 2 is used for Stage 3’s flexible input parameters (“4units_Stephanie Chang_Module5_Stage2_Design Space for GH”). The output evaluation metrics are reported using the ExcelWrite node into the following file (“4units_Stephanie Chang_Module5_Stage3_Design Space for GH_output”). The summary of input parameters and output results is shown in Figure 4’s table. For Stage 3, the grasshopper file with node logic is called: “4units_Stephanie Chang_Module5_Stage3.”
Summary file encompassing both the Stage 3 table (2 flexible inputs: height, top scaling factor) as well as creative bonus table (3 flexible inputs: height, top scaling factor, top rotation factor):
- 4units_Stephanie Chang_Module5_Stage3 + Creative Bonus_Compiled Inputs & Outputs
Point to Ponder: Per building performance criteria, it is favorable to minimize the surface area of the building envelope and maximize the solar insolation potential. From the economic perspective, it is favorable to minimize the cost in which the construction cost per square foot grows linearly from $500/SF at ground level to $1000/SF at 750 ft above ground. Based on maximizing the new metric (gross floor area created / gross surface area of the building envelope), the pair of flexed input values that provides the most desirable result is (height value: 740 ft, top scaling factor: 0.7). I would recommend this building form to the developer since it allows for the best envelope minimization (lowest façade surface area) which can make it a good baseline for then optimizing the solar insolation with orientation, achieves a desired floor area target of 2.72 million SQ which is within 2.5 to 3 million SQ range, and has a relatively stronger taper with a top scaling factor of 0.7 to allow for high elevation floor area reduction to favorably reduce costs (since costs increase with height).
Creative Bonus:
- Grasshopper: created a new building form with 3 flexible inputs, uses Anenome loops, and reports all four evaluation metrics (gross floor area, gross surface area, gross volume, gross floor area created / gross surface area of the building envelope) for 12 test cases (as shown in Figure 5)
- From the evaluation with 12 test cases, an evaluation metric value of 5.46 can be achieved for gross floor area created / gross surface area of building envelope at a height, top scaling factor, and top degree of rotation of 710 ft, 0.7, 120 degrees respectively. This also meets the gross floor area and maximum height constraints.
- In the node logic, color is also added to the model geometry for each evaluation iteration in the run series
- Associated creative bonus files:
- Grasshopper file with node logic:
- 4units_Stephanie Chang_Module5_Stage3_Creative bonus_3parameters
- Flexible input parameters:
- 4units_Stephanie Chang_Module5_Stage3_Design Space for GH_output_creative bonus
- Output evaluation metrics:
- 4units_Stephanie Chang_Module5_Stage3_Design Space for GH_creative bonus